A framework for multidimensional design of data warehouses from ontologies

Some research efforts have proposed the automation of the data warehouse design in order to free this task of being (completely) performed by an expert and facilitate the whole process. Most advanced approaches exclusively work over relational sources and perform a detailed analysis of the data sour...

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Detalles Bibliográficos
Autores: Romero Moral, Óscar|||0000-0001-6350-8328, Abelló Gamazo, Alberto|||0000-0002-3223-2186
Tipo de recurso: informe técnico
Fecha de publicación:2009
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/87149
Acceso en línea:https://hdl.handle.net/2117/87149
Access Level:acceso abierto
Palabra clave:OLAP
Multidimensional Design
Ontologies
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació
Descripción
Sumario:Some research efforts have proposed the automation of the data warehouse design in order to free this task of being (completely) performed by an expert and facilitate the whole process. Most advanced approaches exclusively work over relational sources and perform a detailed analysis of the data sources to identify the multidimensional concepts in a reengineering process. Starting from a logical schema, however, may present some inconveniences. A logical schema is tied to the design decisions made when devising the system and these decisions either made to fulfill the system requirements (for instance, improve query answering, avoid insertion / deletion anomalies, preserve features inherited from legacy systems, etc.) or naively made by nonexpert users, have a big impact on the quality of the multidimensional schemas got by current automatable approaches. In this paper, we introduce our approach for automatically deriving the multidimensional schema from a domain ontology. Our goals are mainly two: i) we want to improve the quality of the output got (by working over a conceptual formalization of the domain instead of a logical one) and ii) we want to automate the process. This second goal is the main reason for choosing ontologies instead of other conceptual formalizations, as ontology languages provide reasoning services that will facilitate the automation of our task.